Embodiments of the invention provide methods and program products for making a recommendation to a purchaser and/or member of a social network.
Social networks provide a forum for individuals, typically connected by some sort of interdependency, to interact. Such interdependencies may include, for example, friendship, kinship, common interest(s), pursuit(s), or belief(s), financial exchange or relationship, etc. Some social networks include recommendation systems designed to compare characteristics of a member of the social network to reference characteristics and then predict a value for a recommendation to be made, i.e., a likelihood that the member would be interested in what is recommended. The recommendation may be almost anything in which the member may be interested, such as a product for purchase, an event the member might attend, an individual with whom the member might wish to connect or otherwise interact, etc.
Many such recommendation systems rely on something selected by the member (e.g., an item purchased) and then recommend to the member other selections made by other members of the social network who have also made the same selection as the member. These and other such recommendation systems consider a plurality of features or characteristics of the selected and unselected items together in calculating a value and determining which items will be recommended. Often, items most similar to those already selected by the member are then recommended to the member. As such, anomalous features or characteristic that may have great significance to a member may be overwhelmed by non-anomalous features, resulting in an item that would be of interest to the member not being included among those items recommended to the member.